AI-Driven Facial Recognition System using Mathematical Feature Extraction

This is a Flask-based facial recognition system that integrates AI-driven models with mathematical feature extraction techniques like Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) to identify faces with high accuracy and performance.

Project Type: Research Thesis
Tech Stack: Python · Flask · PCA · LDA · CNN · SVM · MongoDB

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Features

• Image Capture & Upload
• Facial Preprocessing
• PCA & LDA Feature Extraction
• CNN Model for Deep Feature Learning
• SVM Classifier for Identity Prediction
• Admin Local Server Dashboard for User Upload
• MongoDB/NoSQL Database Integration
• Confidence Score & Identity Verification

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🔧 System Requirements

Hardware

• Intel i5/i7 or AMD Ryzen
• RAM: 8GB+ (16GB Recommended)
• GPU: NVIDIA GTX 1050 or better (optional for training CNN)

Software

• OS: Windows 10/11, MacOS or Ubuntu Linux
• Python 3.8+
• MongoDB or PostgreSQL

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⚙️ Installation Guide

1. Clone the Repository and Set Up Environment

# Clone the repository
git clone https://github.com/0xSettings/AI-Facial-Recognition-Using-Math-Feature.git
cd ai-facial-recognition-using-math-feature

# Create virtual environment
python -m venv venv

# Activate virtual environment
source venv/bin/activate       # For Linux/Mac
venv\Scripts\activate          # For Windows 

# Install all needed dependencies
pip install -r require.txt

# Start MongoDB service
sudo service mongod start      # For Linux/WIndows Powershell user


# Run app
python app.py

# 
# http://127.0.0.1:5000